Abstract:
The easiest way to separate each other's identity in the face. Face recognition is a personal identification system that uses the individual's personal characteristics to identify the person's identity. The human face recognition system is fundamentally in two stages, such as facial detection, where this process is performed very quickly in humans, beyond the conditions in which the objects are located at short distances, the next is the role, which identifies the person face. The stage is then developed as a model of replication and facial recognition models as well as developed by one of the many advanced research bio-metrics technologies and expertise. There are two types of methods that are now popular with advanced face detection patterns, such as eigen faces and fishing methods. For facial recognition, the eigenvalue system is based on face-level space reduction using Principal Component Analysis (PCA) for facial features. Using Eigen's face, the main purpose of using the PCA to detect facial identification (face space) was to detect the highest eigen value associated with the image. Human Face Recognition Using Image Processing of this project with face recognition. The requirements elements of this project are OpenCV and python. For this project we use some keywords such as face recognition, Eigen face, PCA, python, OpenCV. For the extension, there are a large number of applications from this facial recognition project, this project can be extended that different parts and sizes can be detected in different parts of the face.
